Modern control system design is increasingly embracing data-driven methodologies, which bypass the traditional necessity for precise process models by utilising experimental input–output data. This ...

AI will impact every industry and every aspect of society. The pace of AI continues to be relentlessly fueled by new software, hardware, and learning paradigms, and it remains a challenge to meet the ...

Governments around the world are pouring resources into digital health and data systems, hoping that better technology will ...

AI systems are only as fair and safe as the data they’re built on. While conversations about AI ethics often focus on model architecture, algorithmic transparency or deployment oversight, fairness and ...

Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...

The rapid escalation of AI/ML workloads—driven by increasingly large language models—is reshaping high-performance computing and AI data center architectures. Real-time inference and large-scale ...

As agentic AI rapidly expands, proper guardrails — particularly around purpose and data minimization — are necessary to ...